How well do large-eddy simulations and global climate models represent observed boundary layer structures and low clouds over the summertime Southern Ocean?

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

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Reexamining the Relationship between Climate Sensitivity and the Southern Hemisphere Radiation Budget in CMIP Models

Journal of Climate ◽

10.1175/jcli-d-15-0031.1 ◽

2015 ◽

Vol 28 (23) ◽

pp. 9298-9312 ◽

Cited By ~ 17

Author(s):

Kevin M. Grise ◽

Lorenzo M. Polvani ◽

John T. Fasullo

Keyword(s):

Southern Ocean ◽

Southern Hemisphere ◽

Climate Sensitivity ◽

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Radiation Budget ◽

Cmip5 Models ◽

Net Radiation ◽

Subtropical Clouds

Abstract Recent efforts to narrow the spread in equilibrium climate sensitivity (ECS) across global climate models have focused on identifying observationally based constraints, which are rooted in empirical correlations between ECS and biases in the models’ present-day climate. This study reexamines one such constraint identified from CMIP3 models: the linkage between ECS and net top-of-the-atmosphere radiation biases in the Southern Hemisphere (SH). As previously documented, the intermodel spread in the ECS of CMIP3 models is linked to present-day cloud and net radiation biases over the midlatitude Southern Ocean, where higher cloud fraction in the present-day climate is associated with larger values of ECS. However, in this study, no physical explanation is found to support this relationship. Furthermore, it is shown here that this relationship disappears in CMIP5 models and is unique to a subset of CMIP models characterized by unrealistically bright present-day clouds in the SH subtropics. In view of this evidence, Southern Ocean cloud and net radiation biases appear inappropriate for providing observationally based constraints on ECS. Instead of the Southern Ocean, this study points to the stratocumulus-to-cumulus transition regions of the SH subtropical oceans as key to explaining the intermodel spread in the ECS of both CMIP3 and CMIP5 models. In these regions, ECS is linked to present-day cloud and net radiation biases with a plausible physical mechanism: models with brighter subtropical clouds in the present-day climate show greater ECS because 1) subtropical clouds dissipate with increasing CO2 concentrations in many models and 2) the dissipation of brighter clouds contributes to greater solar warming of the surface.

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A synthesis of observations of aerosol-cloud interactions over the pristine, biologically active Southern Ocean and their implications for global climate model predictions

10.5194/egusphere-egu21-8499 ◽

2021 ◽

Author(s):

Isabel L. McCoy ◽

Daniel T. McCoy ◽

Robert Wood ◽

Christopher S. Bretherton ◽

Leighton Regayre ◽

...

Keyword(s):

Southern Ocean ◽

Radiative Forcing ◽

Climate Models ◽

Global Climate ◽

Global Climate Model ◽

Global Climate Models ◽

Biologically Active ◽

Aerosol Cloud ◽

Aerosol Cloud Interactions ◽

Industrial State

<div> The change in planetary albedo due to aerosol-cloud interactions (aci) during the industrial era is the leading source of uncertainty in inferring&#160;Earth's&#160;climate sensitivity to increased greenhouse gases from the historical record. Examining pristine environments such as the Southern Ocean (SO) helps us to understand the pre-industrial state and constrain the change in cloud brightness over the industrial period associated with aci. This study presents two methods of utilizing observations of pristine environments to examine climate models and our understanding of the pre-industrial state. </div><div> First, cloud droplet number concentration (Nd) is used as an indicator of aci. Global climate models (GCMs) show that the&#160;hemispheric contrast&#160;in liquid cloud Nd between the&#160;pristine SO&#160;and the polluted&#160;Northern Hemisphere observed in the present-day can be used as&#160;a proxy for the increase&#160;in Nd from&#160;the pre-industrial. A hemispheric difference constraint&#160;developed from MODIS satellite observations indicates that pre-industrial&#160;Nd may have been higher than previously thought and provides an estimate of radiative forcing associated with aci between -1.2 and -0.6 Wm-2. Comparisons with MODIS Nd &#160;highlight significant GCM discrepancies in pristine, biologically active regions. </div><div> Second, aerosol and cloud microphysical observations from a recent SO aircraft campaign are used to identify two potentially important mechanisms that are incomplete or missing in GCMs: i) production of new aerosol particles through synoptic uplift, and ii) buffering of Nd against precipitation removal by small, Aitken mode aerosols entrained from the free troposphere. The latter may significantly contribute to the high, summertime SO Nd levels which persist despite precipitation depletion associated with mid-latitude storm systems. Observational comparisons with nudged Community Atmosphere Model version 6 (CAM6) hindcasts show low-biased SO Nd &#160;is linked to under-production of free-tropospheric Aitken aerosol which drives low-biases in cloud condensation nuclei number and likely discrepancies in composition. These results have important implications for the ability of current GCMs to capture aci in pristine environments. </div>

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Insights into low-latitude cloud feedbacks from high-resolution models

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2014.0415 ◽

2015 ◽

Vol 373 (2054) ◽

pp. 20140415 ◽

Cited By ~ 95

Author(s):

Christopher S. Bretherton

Keyword(s):

Boundary Layer ◽

Climate Models ◽

Global Climate ◽

Cloud Feedback ◽

Global Climate Models ◽

Limited Area ◽

Slight Reduction ◽

Low Latitude ◽

Cloud Feedbacks ◽

Cloud Regimes

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: ‘thermodynamic’ cloudiness reduction from warming of the atmosphere–ocean column, ‘radiative’ cloudiness reduction from CO 2 - and H 2 O-induced increase in atmospheric emissivity aloft, ‘stability-induced’ cloud increase from increased lower tropospheric stratification, and ‘dynamical’ cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

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The Climatology of the Atmospheric Boundary Layer in Contemporary Global Climate Models

Journal of Climate ◽

10.1175/jcli-d-17-0498.1 ◽

2018 ◽

Vol 31 (22) ◽

pp. 9151-9173 ◽

Cited By ~ 6

Author(s):

Richard Davy

Keyword(s):

Boundary Layer ◽

General Circulation ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

General Circulation Models ◽

Global Climate Models ◽

Cmip5 Models ◽

Seasonal Cycles ◽

Layer Depth

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.

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Southern Ocean deep convection in global climate models: A driver for variability of subpolar gyres and Drake Passage transport on decadal timescales

Journal of Geophysical Research Oceans ◽

10.1002/2015jc011286 ◽

2016 ◽

Vol 121 (6) ◽

pp. 3905-3925 ◽

Cited By ~ 14

Author(s):

Erik Behrens ◽

Graham Rickard ◽

Olaf Morgenstern ◽

Torge Martin ◽

Annette Osprey ◽

...

Keyword(s):

Southern Ocean ◽

Climate Models ◽

Global Climate ◽

Deep Convection ◽

Drake Passage ◽

Global Climate Models

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A Hybrid Cloud Regime Methodology Used to Evaluate Southern Ocean Cloud and Shortwave Radiation Errors in ACCESS

Journal of Climate ◽

10.1175/jcli-d-14-00846.1 ◽

2015 ◽

Vol 28 (15) ◽

pp. 6001-6018 ◽

Cited By ~ 15

Author(s):

Shannon Mason ◽

Jennifer K. Fletcher ◽

John M. Haynes ◽

Charmaine Franklin ◽

Alain Protat ◽

...

Keyword(s):

Southern Ocean ◽

Climate Models ◽

Global Climate ◽

Evaluation Studies ◽

Global Climate Models ◽

Shortwave Radiation ◽

Extratropical Cyclones ◽

Hybrid Cloud ◽

Cloud Parameterization ◽

Cloud Regimes

AbstractA deficit of shortwave cloud forcing over the Southern Ocean is persistent in many global climate models. Cloud regimes have been widely used in model evaluation studies to make a process-oriented diagnosis of cloud parameterization errors, but cloud regimes have some limitations in resolving both observed and simulated cloud behavior. A hybrid methodology is developed for identifying cloud regimes from observed and simulated cloud simultaneously.Through this methodology, 11 hybrid cloud regimes are identified in the ACCESS1.3 model for the high-latitude Southern Ocean. The hybrid cloud regimes resolve the features of observed cloud and characterize cloud errors in the model. The simulated properties of the hybrid cloud regimes, and their occurrence over the Southern Ocean and in the context of extratropical cyclones, are evaluated, and their contributions to the shortwave radiation errors are quantified.Three errors are identified: an overall deficit of cloud fraction, a tendency toward optically thin low and midtopped cloud, and an absence of a shallow frontal-type cloud at high latitudes and in the warm fronts of extratropical cyclones.To demonstrate the utility of the hybrid cloud regimes for the evaluation of changes to the model, the effects of selected changes to the model microphysics are investigated.

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Possible Root Causes of Surface Westerly Biases over the Equatorial Atlantic in Global Climate Models

Journal of Climate ◽

10.1175/jcli-d-12-00226.1 ◽

2013 ◽

Vol 26 (20) ◽

pp. 8154-8168 ◽

Cited By ~ 21

Author(s):

David M. Zermeño-Diaz ◽

Chidong Zhang

Keyword(s):

Boundary Layer ◽

Momentum Flux ◽

Diabatic Heating ◽

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Equatorial Atlantic ◽

Sea Level Pressure ◽

Weak Surface ◽

Zonal Momentum

Abstract Most global climate models (GCMs) suffer from biases of a reversed zonal gradient in sea surface temperature (SST) and weak surface easterlies (the westerly bias) in the equatorial Atlantic during boreal spring. These biases exist in atmospheric GCMs (AGCMs) and are amplified by air–sea interactions in atmospheric–oceanic GCMs. This problem has persisted despite considerable model improvements in other aspects. This study proposes a hypothesis that there are two possible root causes for the westerly bias. The first is insufficient lower-tropospheric diabatic heating over Amazonia. The second is erroneously weak zonal momentum flux (entrainment) across the top of the boundary layer. This hypothesis is based on a scale analysis of a simple model for a well-mixed equatorial boundary layer and diagnoses of simulations from eight AGCMs. Severe westerly biases in AGCMs tend to occur when the diabatic heating at low levels (850–700 hPa) over Amazonia is too weak. Deficient low-level diabatic heating weakens the zonal gradient in sea level pressure along the Atlantic equator, introducing westerly biases. In addition, westerly biases may also occur when easterly momentum flux due to entrainment is underestimated.

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Examining Southern Ocean Cloud Controlling Factors on Daily Time Scales and Their Connections to Midlatitude Weather Systems

Journal of Climate ◽

10.1175/jcli-d-18-0840.1 ◽

2019 ◽

Vol 32 (16) ◽

pp. 5145-5160 ◽

Cited By ~ 7

Author(s):

Mitchell K. Kelleher ◽

Kevin M. Grise

Keyword(s):

Southern Ocean ◽

Time Scales ◽

Vertical Velocity ◽

Climate Models ◽

Global Climate ◽

Controlling Factors ◽

Global Climate Models ◽

Model Errors ◽

Radiative Effects ◽

Daily Time

ABSTRACTClouds and their associated radiative effects are a large source of uncertainty in global climate models. One region with particularly large model biases in shortwave cloud radiative effects (CRE) is the Southern Ocean. Previous research has shown that many dynamical “cloud controlling factors” influence shortwave CRE on monthly time scales and that two important cloud controlling factors over the Southern Ocean are midtropospheric vertical velocity and estimated inversion strength (EIS). Model errors may thus arise from biases in representing cloud controlling factors (atmospheric dynamics) or in representing how clouds respond to those cloud controlling factors (cloud parameterizations), or some combination thereof. This study extends previous work by examining cloud controlling factors over the Southern Ocean on daily time scales in both observations and global climate models. This allows the cloud controlling factors to be examined in the context of transient weather systems. Composites of EIS and midtropospheric vertical velocity are constructed around extratropical cyclones and anticyclones to examine how the different dynamical cloud controlling factors influence shortwave CRE around midlatitude weather systems and to assess how models compare to observations. On average, models tend to produce a realistic cyclone and anticyclone, when compared to observations, in terms of the dynamical cloud controlling factors. The difference between observations and models instead lies in how the models’ shortwave CRE respond to the dynamics. In particular, the models’ shortwave CRE are too sensitive to perturbations in midtropospheric vertical velocity and, thus, they tend to produce clouds that excessively brighten in the frontal region of the cyclone and excessively dim in the center of the anticyclone.

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